Pai 的 AI 雷达

模型与评测

今天:Clean Engineering,GitHub Copilot weekly(Agent 原型)。并行还有 Click here to、Show HN、Terms of Service。

日期
2026/09/06
今日条目
140
当前类目
62
#01

Clean Engineering, Unstable Measurement: A Preregistered Reliability Failure of Black-Box LLM Observers on Shared Endpoints

Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rarely stated assumption: the same request, sent to the same model name, reads the same tomorrow. We audited that assumption in two

推荐理由「Clean Engineering, Unstable Meas…」对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测arxiv cs.AI recent
#02

Clean Engineering, Unstable Measurement: A Preregistered Reliability Failure of Black-Box LLM Observers on Shared Endpoints

Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurement instrument, resting on one rarely stated assumption: the same request, sent to the same model name, reads the same tomorrow. We audited that assumption in two

推荐理由「Clean Engineering, Unstable Meas…」对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.LG
#03

GitHub Copilot weekly releases — August 31

This week, GitHub Copilot expands model choice and content protections, while VS Code adds new ways to manage agent sessions and get pull requests merge-ready. GitHub Copilot, general Claude Fable 5.1 is available to Copilot Pro+, Max, Business, and Enterprise users. Gemini 3.8 F

推荐理由GitHub Copilot weekly releases — August:This week, GitHub Copilot expands model choice and content protections, while VS Code。
模型与评测GitHub Changelog
#07

OpenAI 向 Pro、Enterprise 和 Business Premium 用户推出 GPT-6 Astra,消息额度约为 GPT-5.6 Sol 的一半

OpenAI 通过 ChatGPT Work 和 Codex 向 Pro、Enterprise、Business Premium 计划用户开放 GPT-6 Astra,并通过 API、Microsoft Azure 和 AWS Bedrock 提供。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmto3ih1m016groxt2ypyqos3

推荐理由OpenAI 通过 ChatGPT Work 和 Codex 向 Pro、Enterprise、Business Premium 计划用户开放 GPT-6 Astra,并通过 API。
模型与评测AIHOT feed.xml
#15

Value-Preserving Architectures for Agentic AI Systems

The emergence of agentic AI and LLM-based multi-agent systems (MAS) presents unprecedented opportunities for automating complex tasks, while simultaneously raising critical concerns about the preservation of fundamental human-centered values, such as privacy, fairness, and safety

推荐理由「Value-Preserving Architectures f…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#16

A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors

Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These commands run with host privileges yet ship as lifecycle-hook configuration and may fire at times the LLM never observes. We identif

推荐理由「A Blind Trust, the Bloody Thrust…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#17

Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

Retail supply chain operations rely on coupled decision modules that must adapt as requirements evolve. LLMs offer a natural-language interface for this task, but existing methods primarily focus on individual optimization models. Extending them to heterogeneous decision pipeline

推荐理由「Adapting to Evolving Requirement…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#18

SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents

Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pass functional tests and overlook review-derived acceptance constraints (review constraints) that oft

推荐理由「SWE-Gate: Passing Functional Tes…」偏编码代理,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测arxiv cs.AI recent
#19

SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents

Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated patches pass functional tests and overlook review-derived acceptance constraints (review constraints) that oft

推荐理由「SWE-Gate: Passing Functional Tes…」偏编码代理,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#20

Efficient Test-Time Adaptation through Human-AI Interaction

AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely meet the personal bar professionals need to stake their reputation on. On realistic, open-ended tasks where success criteria are

推荐理由「Efficient Test-Time Adaptation t…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测arxiv cs.AI recent
#21

Efficient Test-Time Adaptation through Human-AI Interaction

AI agents are trained on population-scale data to encode broad capabilities spanning those of many practitioners. Yet the artifacts they produce rarely meet the personal bar professionals need to stake their reputation on. On realistic, open-ended tasks where success criteria are

推荐理由「Efficient Test-Time Adaptation t…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#22

The Natural Language Interaction Protocol and Standard for AI Agents

AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interfaces, protocols, and execution environments. To realize their potential social and business impact, these agents must be able to in

推荐理由「The Natural Language Interaction…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测arxiv cs.AI recent
#23

The Natural Language Interaction Protocol and Standard for AI Agents

AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interfaces, protocols, and execution environments. To realize their potential social and business impact, these agents must be able to in

推荐理由「The Natural Language Interaction…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测papers.cool cs.AI Atom
#24

PatchBench: Evaluating AI Agents for Vulnerability Patching

AI agents have recently demonstrated strong performance in automated vulnerability patching. However, existing evaluations often validate a patch only by testing whether the provided Proof-of-Concept (PoC) input still triggers a crash. This leaves two key threats to validity: age

推荐理由「PatchBench: Evaluating AI Agents…」偏Agent,对造物者有用的是方法能不能迁到自己的 Agent 或生成管线,不是把标题再念一遍。
模型与评测arxiv cs.AI recent